Design of the Model for Predicting Ship Collision Risk using Fuzzy and DEVS

Yi, Mira

doi:10.9709/jkss.2016.25.4.127

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…where D represents the relative distance between two trajectory points, which can be obtained from formula (2). Then, DCPA and TCPA are utilized for assessment of collision risks during vessel navigation and visualization of risk data.…”

Section: Calculation Of Dcpa and Tcpamentioning

confidence: 99%

“…This model comprises 22 terms within five fundamental term sets, each endowed with membership function parameters and a total of 200 fuzzy rules are generated to delineate collision risk levels. Additionally, Mira [2], leveraging fuzzy reasoning and Discrete Event System Specification (DEVS) theory, has proposed a novel model for predicting vessel collision risks while considering general collision avoidance patterns. This innovative model anticipates collision risks by forecasting changes in future vessel movements and validates the functionality of the model structure and fuzzy reasoning module through simulation experiments.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Risk Analysis and Visualization of Merchant and Fishing Vessels Collision In Coastal Waters

Zhu,

Lei,

Wang

et al. 2024

Preprint

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The invasion of ship domain stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validated through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of collision risk. Finally, taking the high risk area of merchant and fishing vessels collision in the Minjiang River Estuary as an example, this paper conduct the analysis involves classifying ship collision scenarios, extracting risk data under different collision scenarios, and visually analyzing areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis is verified by accidents occurred in the recent three years.

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Section: Calculation Of Dcpa and Tcpamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk Analysis and Visualization of Merchant and Fishing Vessels Collision In Coastal Waters

Zhu,

Lei,

Wang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Risk Analysis and Visualization of Merchant and Fishing Vessel Collisions in Coastal Waters: A Case Study of Fujian Coastal Area

Zhu,

Lei,

Wang

et al. 2024

JMSE

View full text Add to dashboard Cite

The invasion of ship domains stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying the collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validates it through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of the collision risk. Finally, taking the high-risk area for merchant and fishing vessel collisions in the Minjiang River Estuary as an example, this paper conducts an analysis that involves classifying ship collision scenarios, extracts risk data under different collision scenarios, and visually analyzes areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis are verified by the number of accidents that occurred in the most recent three years.

show abstract

Design of the Model for Predicting Ship Collision Risk using Fuzzy and DEVS

Cited by 2 publications

References 5 publications

Risk Analysis and Visualization of Merchant and Fishing Vessels Collision In Coastal Waters

Risk Analysis and Visualization of Merchant and Fishing Vessels Collision In Coastal Waters

Risk Analysis and Visualization of Merchant and Fishing Vessel Collisions in Coastal Waters: A Case Study of Fujian Coastal Area

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